How to Clip Videos Offline with a Local LLM (2026)

Most AI clipping tools, like OpusClip, upload your full recording to their servers and charge by the minute of video processed. This guide connects a local LLM through Ollama or LM Studio to the Voice Creator Pro desktop app, so the whole clipping job runs offline on your own computer.

Quick answer

• Install the Voice Creator Pro desktop app and a local LLM server (Ollama or LM Studio).
• Download an instruction-tuned model that fits your memory, and raise its context length so a full transcript fits.
• In the app, open Settings > AI Models, choose Custom endpoint, and set the Base URL: http://localhost:11434/v1 for Ollama or http://localhost:1234/v1 for LM Studio.
• Under Features, set the Viral Clips model to your local model.
• Add a long video, let the local model find the moments, then review and export 9:16 clips.

Skipping the upload matters for client calls, unreleased interviews, internal webinars, legal or medical recordings, and anything under an NDA. It also removes the per-minute meter if you clip hours of streams or podcasts every week. For the general clipping workflow, see how to turn long videos into short clips.

Step 1: Install the desktop app and a local LLM server

You need three things, and both pieces of software install as regular desktop apps.

• The Voice Creator Pro desktop app for Windows or Apple Silicon Macs (see prices). The Microsoft Store version has a free trial.
• A local LLM server that speaks the OpenAI API format. Ollama and LM Studio are two of the most common.
• A model that fits your hardware, covered in Step 2.

Your computer will do two heavy jobs: the video and transcription work in Voice Creator Pro, and the language model. A local LLM uses the same graphics card memory (VRAM) or unified memory the rest of the app wants, so if memory is tight, close other heavy apps while clips generate.

Step 2: Pick a local model that fits your hardware

Choose the largest instruction-tuned model that fits your memory at a context long enough for your typical video. Model names and rankings change every few months, so here is what matters for clipping rather than a named winner:

• Instruction following. Clips asks the model to return structured decisions (which segments, where to cut, what to title them). Models tuned for instructions and structured output handle this far better than small general chat models. If clips come back malformed or empty, a stronger instruction model is usually the fix.
• Context length. The model reads the transcript of your whole video. Pick one whose supported context covers your longest recordings, then make sure your server loads it with that context (the Ollama default on most consumer cards is 4k tokens).
• Memory. The model plus its context must fit in VRAM (or unified memory on a Mac) alongside what Voice Creator Pro needs. Longer context uses more memory, so a model that fits at 4k may not fit at 32k. Quantized versions trade a little quality for a much smaller footprint.
• Speed. A larger model picks better moments but reads the transcript more slowly. That is fine for a weekly podcast; for a dozen streams a day, a smaller, faster model may suit you better.

Then run one real recording through Clips and compare the moments it picks against what you would have chosen.

Step 3: Connect Ollama or LM Studio

In the desktop app, both servers connect through Settings > AI Models as a Custom endpoint. The full reference for these settings is in the docs page on connecting an LLM.

Option A: Ollama

Ollama runs models in the background and exposes an OpenAI-compatible API at http://localhost:11434/v1. Its documentation says a client must send an API key but that Ollama ignores it, so any placeholder value works.

1. Install Ollama from ollama.com/download. It is available for Windows, macOS, and Linux.
2. Download a model from a terminal with ollama pull <model-name>, using a model from the Ollama library that fits your memory.
3. Raise the context length. Use the slider in the Ollama app settings, or start the server with OLLAMA_CONTEXT_LENGTH set (for example OLLAMA_CONTEXT_LENGTH=32000 ollama serve). Run ollama ps to check the context the model actually loaded with.
4. Open Voice Creator Pro, go to Settings > AI Models, and set Provider to Custom endpoint.
5. Set the Base URL to http://localhost:11434/v1.
6. Fill the API key field with a placeholder such as ollama.
7. Under Features, set the Viral Clips model to the model you pulled. Use the refresh button next to the model field to load the list from Ollama.

Ollama sets context length from your VRAM: 4k tokens on cards under 24 GB, 32k from 24 to 48 GB, and 256k at 48 GB and above. An hour of conversation is roughly 9,000 spoken words, which is more than a 4k context holds.

Option B: LM Studio

LM Studio is a desktop app for downloading and chatting with models, with a built-in server. Its OpenAI-compatible API runs at http://localhost:1234/v1 by default, and it does not require authentication unless you turn that on.

1. Install LM Studio from lmstudio.ai and download a model from its search screen.
2. Set the context length. In the My Models tab, click the gear icon on the model and raise its context size so a full transcript fits.
3. Start the server. Open the Developer tab and toggle Start server on, or run lms server start from a terminal.
4. Open Voice Creator Pro, go to Settings > AI Models, and set Provider to Custom endpoint.
5. Set the Base URL to http://localhost:1234/v1.
6. Fill the API key field with any placeholder value if the app asks for one.
7. Under Features, set the Viral Clips model, using the refresh button to load LM Studio's model list.

Step 4: Generate your first offline clips

With the model connected, the clipping workflow is the same as with any provider:

1. Add your long video. Upload the file. (Clips on desktop can also take a YouTube link, but downloading from YouTube needs an internet connection.)
2. Set the clip options: minimum and maximum clip length in seconds, the maximum number of clips, and an optional Guide the AI prompt, such as "focus on the parts about pricing" or "pick moments with a strong opinion".
3. Let the AI find the moments. This is the step that runs on your local LLM, and it takes longer than with a cloud model.
4. Review each clip in the editor. Hook sets the on-screen hook line, Subtitles styles the captions, Transcript shows what was said, and Effects sets the framing (Auto, Speaker focus, Blurred background, Split screen, or Cut between speakers), toggles cutting pauses and breaths, and adds Punch in, Color pop, Black and white, Flash, and Vignette.
5. Export in vertical 9:16 for TikTok, Instagram Reels, and YouTube Shorts.

The Guide the AI prompt matters more with a local model than a cloud one. A large cloud model can usually infer what a good clip looks like on its own; a smaller local model does noticeably better when you tell it what you want.

You can also dub a finished clip into any of 21 languages from the same editor, and the docs on video dubbing explain how it works.

Why clipping needs an LLM

An AI clipper does three kinds of work, and they need different tools:

1. Transcribing the speech so the software knows what was said and when.
2. Deciding what is worth clipping, which means reading the transcript and judging which stretches stand on their own, have a hook, and land a point.
3. Cutting, framing, captioning, and exporting the result.

The Voice Creator Pro desktop app handles steps 1 and 3 on your computer. Step 2 needs a large language model (LLM). In Clips, the LLM:

• Finds the moments worth clipping in the long video.
• Makes the auto-edit decisions, such as where to place zoom-ins and which filler words and silences to cut.
• Writes the titles and captions to post alongside each clip.

VCP Cloud has an LLM built in. On the desktop app you connect your own in Settings > AI Models: OpenAI, Google Gemini, OpenRouter, DeepSeek, or a Custom endpoint that accepts any OpenAI-compatible API by its base URL.

With a cloud provider, your video's transcript is sent to that provider. Point the custom endpoint at an LLM on your own machine, and nothing leaves it.

Three ways to run Clips

	Desktop + local LLM	Desktop + cloud LLM key	VCP Cloud
Video processed on	Your computer	Your computer	Our servers
Transcript goes to	Stays on your computer	Your LLM provider	Our servers
Works offline	Yes, fully	No, the LLM step needs internet	No
Setup	App, local LLM server, model	App, API key	None, runs in your browser
LLM cost	None beyond your hardware	Your provider's rates	Included
Moment-picking quality and speed	Depend on your hardware	Strong with large models, fast	Built-in LLM, fast
App cost	One-time purchase	One-time purchase	Free tier with watermarked clips, paid plans

The honest tradeoffs

Running everything locally is the right call for private footage and heavy volume, but it comes with real costs:

• It is slower. A local model on a consumer GPU reads a long transcript much more slowly than a cloud API, and on a CPU-only machine it can be very slow.
• The picks can be weaker. The large models behind cloud APIs are generally better at judging which moment will hold attention. A local model may choose flatter moments, miss a strong hook, or write blander titles, so plan to review more of its choices.
• Hardware sets the ceiling. Which model you can run, and at what context length, depends on your VRAM or Mac memory. The app runs on NVIDIA, AMD, or Intel Arc cards (8 GB of VRAM recommended), Apple Silicon Macs, or the CPU alone, more slowly, but the LLM on top needs its own room.
• You manage the setup. Model downloads, context settings, and keeping the server running are on you.

If privacy is the reason you are here, a middle path is a local LLM for sensitive recordings and a cloud key for everything else. You can switch providers in Settings > AI Models at any time.

When VCP Cloud is the better fit

If your footage is not sensitive and you just want clips, VCP Cloud does all of this in your browser with a built-in LLM, so there is no model, server, or context length to set up. The free tier includes Clips with watermarked exports, and paid plans remove the watermark (see pricing).

VCP Cloud is not offline, since your video is processed on our servers, but it is never used to train models. For a wider look at the options, see the best AI clip makers, our OpusClip alternatives, and the Clips product page.